ToRA is a tool-integrated reasoning agent designed to solve challenging mathematical problems by combining large language model reasoning with external tool interactions. The agent is trained to decide when to invoke tools such as code executors, retrieve relevant information, and incorporate tool outputs back into the reasoning chain. It includes training pipelines, inference code, and benchmark evaluations across mathematical reasoning datasets.